The expectation and the variance of the syndrome weight distribution of linear codes after transmission of codewords through a binary symmetric channel are derived exactly in closed form as functions of the code's parity-check matrix and of the degree distributions of the associated Tanner graph. The influence of (check) regularity of the Tanner graph is studied. Special attention is payed to Tanner graphs that have no cycles of length four. We further study the equivalence of some classes of combinatorial designs and important classes of LDPC codes and apply our general results to those more specific structures. Simulations validate the analytical results and show that the actual cumulative distribution function of the syndrome weight is close to that of a normal distribution.
The expectation and the variance of the syndrome weight distribution of linear codes after transmission of codewords through a binary symmetric channel are derived exactly in closed form as functions of the code's parity-check matrix and of the degree distributions of the associated Tanner graph. The influence of (check) regularity of the Tanner graph is studied. Special attention is payed to Tanner graphs that have no cycles of length four. We further study the equivalence of some classes of combinatorial designs and important classes of LDPC codes and apply our general results to those more specific structures. Simulations validate the analytical results and show that the actual cumulative distribution function of the syndrome weight is close to that of a normal distribution.
In this paper, we study binary low-density parity-check, or LDPC codes, determined by the adjacency matrices of the odd graphs as their parity-check matrices. We show that for the odd graph $ O_n $, $ n\geq 3 $, the obtained code $ C_n $ is an $ (n, n) $-regular binary LDPC code of length $ {2n-1 \choose n-1} $, dimension $ {2n-2 \choose n-2} $ and minimum distance $ n+1 $. Further, we show that the girth of the corresponding Tanner graph determined by the adjacency matrix of an odd graph is equal to 6, and give the expression for the variance of the syndrome weight for $ C_n $. Moreover, we show that there are no absorbing sets of size smaller than 3 for these codes and that the absorbing sets of size 3 exist only for $ n = 3 $. Additionally, we give the structure of $ (a, b) $ absorbing sets with $ b \leq a\leq n $. Finally we prove that $ C_n $ is also a linear code with complementary dual, or LCD code, for $ n\geq3 $.
We address the problem of evaluating the asymptotic normalized distributions of a class of combinatorial configurations in random, regular, binary low-density parity-check (LDPC) code ensembles.Among the configurations considered are trapping and stopping sets 1 ; these sets represent induced subgraphs in the Tanner graph of a code that, for certain classes of channels, exhibit a strong influence on the height and point of onset of the error-floor.The techniques used in the derivations are based on large deviation theory and statistical methods for enumerating random-like matrices.These techniques can also be applied in a setting that involves more general structural entities such as subcodes and/or minimal codewords, which are known to characterize other important properties of soft-decision decoders of linear codes.
In this paper, we study the cycle distribution of random low-density parity-check (LDPC) codes, randomly constructed protograph-based LDPC codes, and random quasicyclic (QC) LDPC codes. We prove that for a random bipartite graph, with a given (irregular) degree distribution, the distributions of cycles of different length tend to independent Poisson distributions, as the size of the graph tends to infinity. We derive asymptotic upper and lower bounds on the expected values of the Poisson distributions that are independent of the size of the graph, and only depend on the degree distribution and the cycle length. For a random lift of a bi-regular protograph, we prove that the asymptotic cycle distributions are essentially the same as those of random bipartite graphs as long as the degree distributions are identical. For random QC-LDPC codes, however, we show that the cycle distribution can be quite different from the other two categories. In particular, depending on the protograph and the value of c, the expected number of cycles of length c, in this case, can be either 8(N) or 8(1), where N is the lifting degree (code length). We also provide numerical results that match our theoretical derivations. Our results provide a theoretical foundation for emperical results that were reported in the literature but were not well-justified. They can also be used for the analysis and design of LDPC codes and associated algorithms that are based on cycles.
LDPC(Low Density Parity Check) codes are described by bipartite graphs with bit nodes and parity-check nodes. Tanner derived minimum distance bounds of the regular LDPC code in terms of the eigenvalues of the associated adjacency matrix. In this paper we generalize the Tanner's results. We derive minimum distance bounds applicable to both regular and blockwise-irregular LDPC codes. The first bound considers the relation between bit nodes in a minimum-weight codeword, and the second one considers the connectivity between parity nodes adjacent to a minimum-weight codeword. The derived bounds make it possible to describe the distance property of the code in terms of the eigenvalues of the associated matrix.
We consider coded data transmission over a binary-input output-symmetric memoryless channel using a binary linear code. In order to understand the performance of maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's attention needs to be shifted to the pseudo-codewords, in particular, to the minimal pseudo-codewords and their pseudo-weights. In this paper, we investigate some families of codes that have good properties under LP decoding, namely certain families of low-density parity-check (LDPC) codes that are derived from projective and Euclidean planes: we study the structure of their minimal pseudo-codewords and give lower bounds on their pseudo-weight. Besides this main focus, we also present some results that hold for pseudo-codewords and minimal pseudo-codewords of any Tanner graph, and we highlight how the importance of minimal pseudo-codewords under LP decoding varies depending on which binary-input output-symmetric memoryless channel is used.
In this paper, time-invariant spatially coupled low-density parity-check convolutional codes (SC-LDPC-CCs) are considered, and the connections existing between their low-weight codewords and cycles in their Tanner graphs are studied. Using the polynomial representation of these codes, we show that parity-check matrices having columns with weight ≥2 can be analyzed considering a certain number of parity-check sub-matrices having regular columns with weight 2. These sub-matrices are associated to cycles in the code Tanner graph and define as many codes we denote as component codes. Based on this observation, we find that codewords of the main code can be expressed as combinations of codewords of the component codes. The design of codes free of codewords up to a certain weight is also addressed. We show that low-weight codewords in the main code can be avoided by removing some types of cycles in its Tanner graph. Our design approach is applied to some well-known ensembles of SC-LDPC-CCs to prove its effectiveness.